A location analysis approach for military maintenance scheduling with geographically dispersed service areas

This research uses a two-stage maximal covering location problem (MCLP) model to develop Inter continental ballistic missile (ICBM) maintenance schedules for the US Air Force. Solutions are compared to actual missile maintenance activities accomplished at F. E. Warren Air Force Base (AFB), Wyoming in May 2005. Sensitivity analysis is performed to determine the impact of altering security response times and the number of security patrol areas on the quality of daily maintenance schedules and personnel usage. Results indicate marked improvement over traditional Air Force scheduling methods. In addition sensitivity analysis identifies the levels at which the quality and quantity of maintenance performance is impacted.     

A note towards improved homeland defense

We indicate a number of shortcomings in the second stage in the approach of Bell et al. [1] that may lead to unsatisfactory results. Some possible remedies are investigated.     

Location optimization of strategic alert sites for homeland defense

This research uses a location analysis approach for selecting aircraft alert sites for the defense of important national areas of interest identified by the US Department of Defense. Solutions are generated in a two step approach where the minimum number of sites is first identified using the location set covering problem and then the result is improved by finding the minimum aggregate network distance or p-median solution from the alternate optimal solutions to the LSCP. This approach also identifies the p-center solution to the problem ensuring equitable response to all areas of interest. Sensitivity analysis is performed to determine the impact of altering aircraft launch and flying times on the number of required alert sites and the amount of coverage provided by selecting fewer locations. Results indicate a significant increase in the number of alert locations needed in comparison to original military estimates. The research points out significant implications about future military base closure decisions and the trade-offs between cost and required response times of aircraft in a defense emergency.     

A comparison of simplified value function approaches for treating uncertainty in multi-criteria decision analysis

Uncertainty is present in many decisions where an action's consequences are unknown because they depend on future events. Multi-attribute utility theory (MAUT) offers an axiomatic basis for choice, but practitioners may prefer to use simpler decision models for transparency, ease of use, or other practical reasons. We identify some ‘simplified’ models currently in use and use a simulation experiment to evaluate their ability to approximate results obtained using MAUT. Our basic message is that avoiding assessment errors in the application of a simplified model is more important than the choice of a particular type of model, but that the best performance over a range of decision problems is from a model using a small number of quantiles.     

Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach

We consider resource allocation problems where inputs are allocated to different entities such as activities, projects or departments. In such problems a common goal is achieving a desired balance in the allocation over different categories of the entities. We propose a bi-criteria framework for trading balance off against efficiency. We define and categorise indicators based on balance distribution and propose formulations and solution algorithms which provide insight into the balance-efficiency tradeoff. We illustrate our models by applying them to the data of a portfolio selection problem faced by a science funding agency and to randomly generated large-sized problem instances to demonstrate computational feasibility.     

A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand

This paper describes an employee scheduling system for retail outlets; it is a constraint-based system that exploits forecasts and stochastic techniques to generate schedules meeting the demand for sales personnel. Uncertain scenarios due to fluctuating demand are taken into account to develop a stochastic operational optimization of staffing levels. Mathematically, the problem is stated as a mixed-integer linear programming problem. Simulations with store data belonging to a major Swiss retailer show the effective performance of the proposed approach. The schedule quality is assessed through comparison with a deterministic scheduling package, which has been used at several outlets in Switzerland.     

Retail category management: State-of-the-art review of quantitative research and software applications in assortment and shelf space management

Retail requires efficient decision support to manage increasing product proliferation and various consumer choice effects with limited shelf space. Our goal is to identify, describe and compare decision support systems for category planning. This research analyzes quantitative models and software applications in assortment and shelf space management and contributes to a more integrated modeling approach. There are difficulties commonly involved in the use of commercial software and the implementation and transfer of scientific models. Scientific decision models either focus on space-dependent demand or substitution effects, whereas software applications use simplistic rules of thumb. We show that retail assortment planning models neglect space-elastic demand and largely also ignore constraints of limited shelf space. Shelf space management streams on the other hand, mostly omit substitution effects between products when products are delisted orout-of-stock, which is the focus of consumer choice models in assortment planning. Also, the problem sizes of the models are often not relevant for realistic category sizes. Addressing these issues, this paper provides a state-of-the-art overview and research framework for integrated assortment and shelf space planning.     

Policies for knowledge refreshing in databases

Knowledge discovery in databases (KDD) provides organizations necessary tools to sift through vast data stores to extract knowledge. This process supports and improves decision making in organizations. In this paper, we introduce and define the concept of knowledge refreshing, a critical step to ensure the quality and timeliness of knowledge discovered in a KDD process. This has been unfortunately overlooked by prior researchers. Specifically, we study knowledge refreshing from the perspective of when to refresh knowledge so that the total system cost over a time horizon is minimized. We propose a model for knowledge refreshing, and a dynamic programming methodology for developing optimal strategies. We demonstrate the effectiveness of the proposed methodology using data from a real world application. The proposed methodology provides decision makers guidance in running KDD effectively and efficiently.     

基于Agent的情感劝说的决策过程及模型研究

Agent具有情感后进行的劝说决策会更加理性,而现有研究还不够全面深入。针对此问题,首先结合形式逻辑理论,定义了基于Agent的情感劝说及其决策过程,并将基于Agent的情感劝说的决策过程划分为评价情感劝说行为、更新情感劝说状态、调整情感劝说目标、产生情感劝说行为四个阶段;其次针对这四个阶段,结合OCC情感模型和PAD心情模型,运用多属性效用理论,引入情感淡化因子和情感评价因子,定义了Agent情感触发函数,建立了八种Agent基本情感与劝说目标的映射关系,将Agent的情感劝说行为分为奖励型、申辩型、威胁型和反辩型四类,分别构建了相应的决策模型,从而构成了更加完整和合理的基于Agent的情感劝说的决策过程模型;最后通过算例证明了模型的合理性和有效性。     

多任务业务外包的激励契约

多任务业务外包有助于发包企业充分利用外部资源.通过设计面向多任务的激励契约,平衡接包企业在各项任务之间的投入,能够改善外包效率.运用均方效用函数方法,构建了多任务委托代理模型,通过敏感性分析讨论了外生参数的变化对激励契约的影响,并在任务无关、互补和替代三种情形下考察了模型的应用.研究发现对特定任务的激励,不仅受到接包企业风险偏好和与此任务有关的参数变化的影响,还受到与其它任务有关的参数变化的影响,其中影响的方向和强度分别依赖于任务之间的关联属性和关联程度.研究结论为发包企业利用各种属性指标,尤其是任务关联性质,加强对多任务外包的激励管理具有借鉴意义.     

IT security planning under uncertainty for high-impact events

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.     

Incorporating preference information in interactive reference point methods for multiobjective optimization

In this paper, we introduce new ways of utilizing preference information specified by the decision maker in interactive reference point based methods. A reference point consists of desirable values for each objective function. The idea is to take the desires of the decision maker into account more closely when projecting the reference point onto the set of nondominated solutions. In this way we can support the decision maker in finding the most satisfactory solutions faster. In practice, we adjust the weights in the achievement scalarizing function that projects the reference point. We identify different cases depending on the amount of additional information available and demonstrate the cases with examples. Finally, we summarize results of extensive computational tests that give evidence of the efficiency of the ideas proposed.     

BlueLinx can benefit from innovative inventory management methods for commodity forward buys

Commodity prices often fluctuate significantly from one purchasing opportunity to the next. These fluctuations allow firms to benefit from forward buying (buying for future demand in addition to current demand) when prices are low. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. We compare our heuristic with existing methods via simulation using real demand data from BlueLinx, a two-stage distributor of building products. The results show that our combined heuristic performs better than any existing methods considering forward buying or safety stock separately. We also compare our heuristic to the optimal inventory management policy by full enumeration for a smaller data set. The proposed heuristic is shown to be close to optimal. This study is the first to decide both the optimal number of future periods to buy for uncertain purchase price and the appropriate purchasing quantity with safety stock for uncertain demand simultaneously. The experience suggests that the proposed combined heuristic is simple and can be very beneficial for any company where forward buying is possible.     

信息不对称下医药营销服务外包契约设计

为了缩减销售成本,一些制药企业将营销服务外包给合约销售公司(contract sales organization,CSO).由于CSO的营销努力不可合同化,制药企业需要基于市场销量来激励CSO的营销努力.然而,市场销量受制药企业定价决策的影响,因此CSO将面临制药企业提高定价的道德风险.此外,药品营销难度信息可能是CSO的私人信息,这使得制药企业面临逆向选择问题.当制药企业将营销服务外包给多个CSO时,由于制药企业针对同一药品在不同市场的售价相同,其定价决策对多个CSO所服务市场的销量具有共同的影响.相对绩效的激励契约能够消除共同不确定因素对代理人产出的影响,从而更有利于激励代理人付出高水平的努力.因此依据信息甄别的博弈模型,分析基于个体绩效与基于相对绩效的激励契约的有效性.研究发现:1)药品营销难度信息对称时,基于相对绩效的激励契约占优于基于个体绩效的激励契约,且可以获得全局最优的营销努力和期望利润;2)药品营销难度信息不对称时,两种激励契约均不能获得全局最优的营销努力和期望利润.数值分析表明,药品营销难度的先验概率,市场价格敏感性和高低类型药品营销难度差异的变化会影响制药企业的契约选择,较高的市场价格敏感性和较低的高低类型药品营销难度差异使得基于相对绩效的激励契约更有效.     

Process Tracing Analysis of Hurricane Information Displays

To study people's processing of hurricane forecast advisories, we conducted a computer‐based experiment that examined 11 research questions about the information seeking patterns of students assuming the role of a county emergency manager in a sequence of six hurricane forecast advisories for each of four different hurricanes. The results show that participants considered a variety of different sources of information—textual, graphic, and numeric—when tracking hurricanes. Click counts and click durations generally gave the same results but there were some significant differences. Moreover, participants’ information search strategies became more efficient over forecast advisories and with increased experience tracking the four hurricanes. These changes in the search patterns from the first to the fourth hurricane suggest that the presentation of abstract principles in a training manual was not sufficient for them to learn how to track hurricanes efficiently but they were able to significantly improve their search efficiency with a modest amount (roughly an hour) of practice. Overall, these data indicate that information search patterns are complex and deserve greater attention in studies of dynamic decision tasks.     

Risks in offshore IT outsourcing: A service provider perspective

Offshore outsourcing of Information Technology (IT) services is the prevalent practice in global businesses today. Despite the strategic advantages and cost benefits that offshore outsourcing offers, outsourcing relationships also involve risks, for both the client, as well as the service provider – a fact that is evidenced by the reported failures of such engagements. Some of the prior researches in this area have focused on identifying various types of client risks and their sources. However, the study of risks from a service provider’s perspective has not received due treatment in literature. This study analyses offshore IT outsourcing risks from the perspective of service providers. A case based approach using the principles of grounded theory was used for studying the risks. Theoretical sampling was used to collect data from 5 mid-tier offshore third party service providers based in Bangalore, India. From our coding and analysis three broad categories of service provider risks emerged, namely, macroeconomic, relationship specific and project specific. Relationship maturity, nature of contract, nature of service or project and nature of client were identified as contextual factors which influence the degree of risk.     

Third-party logistics selection problem: A literature review on criteria and methods

This paper presents a literature review on Third-Party Logistics (3PL) selection decision in terms of criteria and methods. Based on the analysis of 67 articles published within 1994–2013 period, this review reveals that 3PL selection is empirical in nature and is related to a region/country, industrial sector, and logistics activities outsourced. In terms of 3PL selection criteria, 11 key criteria are identified; each one is defined by a set of attributes. Cost is the most widely adopted criterion, followed by relationship, services, and quality. In terms of methods for 3PL evaluation, they can be categorized in 5 groups, namely: MCDM techniques, statistical approaches, artificial intelligence, mathematical programming, and hybrid methods.     

Incentive issues in performance-based outsourcing contracts in the UK defence industry: a simulation study

Traditional outsourcing literature has claimed gains for the customer in terms of quality and costs. However, such gains are illusory in outsourcing of high-risk, complex tasks. The use of contracts and governance mechanisms for handling complex procurements is essential in obtaining rewards from outsourcing. Powerful incentives and risks are normally used in industrial service contracts to transfer risks to measure compliance with performance measures. The availability contracts for complex engineering services provision are forms of outsourcing contracts that transfer resources from government to external service providers on a substantial scale. The change moves the contractor role from creating resources to managing resources. Such role change mandates collaboration with customers and suppliers in supply/value chains. The management task is then perceived in terms of linking and optimising alignments rather than increasing service levels. Incentive design is one mechanism for linking the coordination of resources required in availability contracting to the business model. This article studies the impacts of agreed contract type and incentive mechanism on the customer and service provider profits using agent-based discrete event simulation model under multiple risk sharing scenarios.